Method for segmenting a video image into elementary objects

ABSTRACT

The invention concerns a method for segmenting video images into elementary objects. Said method consists in defining (A) an initial boundary (CD) entirely surrounding the object (OBJ); defining (B), on the basis of the initial boundary (CD), an original active boundary (CAO) constituting of a set of nodes, each formed by a point of said contour and an elastic energy function representing the distance separating said node and a neighbouring node; subjecting (C) the original active boundary (CAO) to a convergent deformation, (D) by moving at least one node towards the natural boundary (CN) of the elementary object to obtain a current active contour (CAC); subjecting each current active boundary (CAC) to a deformation by iterations (E) as long as the condition is fulfilled, to obtain a final active boundary substantially identical to the object natural boundary. The invention is useful for processing fixed or video images.

[0001] The invention relates to a method for segmenting a video imagebased on elementary objects.

[0002] At present, it is completely impossible to reproduce thefunctioning of the human visual and cognitive system using proceduresfor segmenting video images based on elementary objects emanating fromcomputer-based vision processes. Specifically, the resulting imageobtained by virtue of the implementation of the aforesaid processes isunder-segmented or over-segmented. In neither case do these proceduresallow automatic reproduction of the ideal segmentation carried out by ahuman operator.

[0003] Nevertheless, numerous applications have recourse tosegmentation, which, in order to appear ideal, ought to be robust, fast,discriminating and nonspecific to a particular field of application.More particularly, the automatic following or calculation, with a viewto the acquisition and tracking, of the trace of an object over time ina succession of video images remains a completely open problem, all themore so when the object may deform via complex transformations overtime, natural or artificial transformations such as “morphing”.

[0004] Among the image segmentation procedures proposed hitherto,several families are customarily distinguished.

[0005] A first family corresponds to the conventional segmentationprocedures based on filtering, mathematical morphology, region growth,partition of color histograms, Markov procedures. These automaticprocedures are applied to an image but the results obtained dependstrongly on the particular content of the image and are sensitive to thetexture of the image. They do not allow segmentation of the image basedon elementary objects in so far as it is difficult to retrieve thecontours of an object of interest. The images are over-segmented and thecontours detected do not all form a closed list, substantiallyguaranteeing the integrity of the contour of the object of interest andthe segmentation of the latter. The scatter in the results is largebetween the various procedures and the results are not very robust, twovery similar images possibly culminating in a very differentsegmentation and vice versa one and the same image possibly culminatingin a very different segmentation with two procedures.

[0006] A second family groups together procedures based on mathematicalmorphology and which try to remedy the problems and the drawbacks of theprocedures of the first family using processes based on a treestructure, a binary partition tree making it possible to characterizethe content of the images. Such a tree structure describing the spatialorganization of the image is obtained by iteratively merging neighboringregions according to a homogeneity criterion until a single region isobtained. The tree is constructed by preserving the trace of mergedregions at each iteration of the process. This procedure offers thepossibility of manually marking regions of interest on the originalimage and of retrieving nodes corresponding to this marking from thepartition tree. The drawbacks of the procedures of this family reside inthe fact that the entire image is segmented, that it is necessary tohave prior knowledge of the number of regions constituting the object,and that the contours of the object which are obtained are not accurateenough or are not the right ones. Specifically, it often happens thatthe object of interest straddles several regions, the contours of theobject, in such a case, therefore not corresponding to the contours ofthese regions.

[0007] A third family groups together statistical procedures based onMarkov fields. These procedures carry out a tagging of the regions ofthe image according to a criterion to be maximized. They can takeaccount of a wide set of a priori information about the image and areparticularly suited to satellite images composed of textured andjuxtaposed zones.

[0008] A fourth family relates to active contour procedures alsodesignated snake. In this type of procedure, described in the articleentitled “Snake: Active Contour Models”, published by M KASS, A. WITKINand D. TERZOPOULOS in the International Journal of Computer Vision, vol.1, pp. 321-332, 1998, the principle consists in iteratively deforming aninitial curve until it hugs the content of the object, by minimizing anenergy functional. This energy is composed of two terms:

[0009] the internal energy of the contour, which energy depends on theintrinsic or geometrical properties of the active contour, such aslength, curvature, etc. This internal energy term allows a contractionof the active contour around the object and causes a displacement of thelatter's nodes in a direction which locally minimizes the energy;

[0010] the energy external to the contour, which energy corresponds to aterm bound to the data. This external energy term is generally linkedwith the contours present in an image and slows down the contraction ofthe active contour around these contours present.

[0011] It is noted in particular that this family of procedures involvesa priori knowledge of the contours present in the image, somethingwhich, of itself, can be achieved only by virtue of a priori analysis ofthe image.

[0012] A fifth family of procedures corresponds to a development of theprocedure of the previous family, in which development, as far as theexternal forces applied to the active contour are concerned, the modelbehaves like a balloon inflating under the effect of the aforesaidforces and stops when it encounters marked or predefined contours. Thus,the active contour can overstep contours which are not very marked.Other developments have proposed the use of deformable geometric activecontours. These developments use level sets allowing automaticmanagement of the changes of topology of the active contour. However,the procedures of the aforesaid family necessarily require aninitialization which is close to the final solution, that is to say tothe natural contour of the object, in order to obtain good convergenceof the algorithm.

[0013] A sixth family of procedures is based on the definition ofregions of the image, by prior estimation of these regions and of thebackground of the image. The curve of the evolution of the activecontour is generally defined by deriving a criterion in thedistributions sense. This criterion depends on constraints relating totwo sets: the background of the image and the objects in motion. Theevolution curve can comprise the following three terms:

[0014] a term bound to the data;

[0015] a hyperbolic term, allowing adaptation to the shape of theobjects, and

[0016] a parabolic term stabilizing the solution by smoothing thecontours.

[0017] The direction of motion of the active contour varies over time,allowing the active contour to dilate or, conversely, to contract atcertain nodes. However, these procedures require a labeling of thebackground of the image and the execution time remains too large, of theorder of several minutes, for dynamic applications to moving objects ofvideo images.

[0018] As far as the procedures for following objects in the image areconcerned, also known as tracking procedures, various families ofprocedures are currently proposed.

[0019] A first family calls upon a meshing technique. According to afirst procedure of this family, a hierarchical meshing structuresuccessively estimates the dominant motion of the object, then thelatter's internal motions. A hierarchy of meshes is generated from themask of the object defining a polygonal envelope of this object. Beforecommencing the hierarchical cycle of motion estimation, an affine globalmodel initializing the coarse mesh of the hierarchy is estimated. Thisestimation is then propagated to the finest levels where a globalestimation is carried out. It sometimes happens that a node strays fromthe natural contour of the object and attaches itself to the backgroundof the scene, dragging its neighboring nodes with it. This draggingprocess is linked to a temporal accumulation of errors of positioning ofthe nodes, since only the initial segmentation is available duringoptimization. To remedy the aforesaid dragging process, a solution hasbeen proposed which consists in furthermore injecting a procedure muchlike the active contours procedure. Active contours are generated fromthe finest mesh of the hierarchization cycle and they evolve over thecontours emanating from the segmented current image. These activecontours are injected after the first estimation of the motion so as toconstrain the vertices of the edges of the mesh to reposition themselveson the outer contours of the object. This solution has not however, beenadopted, since the mesh structure is then very complex to use.

[0020] A second family calls upon the implementation of active contours,according to the procedures described above. The active contour obtainedon the current image is propagated from one image to the next anddeforms so as to hug the contours of the object of interest on thesuccessive images. Motion constraints can be added during theminimization of the energy functional.

[0021] These procedures can furthermore combine procedures forestimating parameters based on optical flow or based on a model ofmotion, such as translation, affine transformation, perspective,bilinear deformation or the like, and active contour procedures, withthe aim of making object tracking or following more robust. In aspecific example, the object following procedure combines an activecontour procedure and an analysis of the motion based on regions of theimage. The motion of the object is detected by a motion-basedsegmentation algorithm. An active contour model is then used with theaim of following and segmenting the object. Thereafter, the motion ofthe region defined inside the active contour is then estimated by amulti-resolution approach based on an affine model. A Kalman filter isused to predict the position of the aforesaid region and hence toinitialize the active contour in the next image.

[0022] A third family of procedures calls upon techniques based on tagmaps, which utilize the image partitioning processes, or tag maps overthe pixels of an image. In a first procedure, a technique combininginformation regarding motion and spatial organization over the imageshas been proposed with the aim of following an object. The current imageis partitioned by a mathematical morphology procedure and the resultingimage is compensated by the motion vectors estimated coarsely by a blockmatching algorithm. The spatial homogeneity of the regions or markers isverified thereafter. These procedures have the limitations ofconventional active contour procedures, in particular slowness ofconvergence. A second procedure is based on the technique of Markovfields. This procedure comprises a procedure for segmenting an imageinto regions which are homogeneous in the motion sense by statisticaltagging. The partition is obtained according to a criterion ofintensity, color and texture. A third procedure carries out a spatialsegmentation of the image into homogeneous regions and tracking iscarried out by a back-projection procedure. This involves determiningthe mask of the object of interest on the current image. Each region ofthe segmented current image is then back-projected according to themotion onto the previous segmented image. The back-projected regionsbelonging to the mask of the object then form the new mask of the objecton the current image. These procedures have the drawback of yieldingrather inaccurate object contours. Specifically, holes or artefactsappear, because of the use of an initial segmentation of the image.

[0023] The object of the present invention is to remedy the drawbacks ofthe aforesaid techniques of the prior art, both as regards the imagesegmentation process and the tracking or following of an object inmotion over successive images.

[0024] In particular, an object of the present invention is theimplementation of a method for segmenting a video image based onelementary objects in which method no a priori knowledge about the imageis required.

[0025] Another object of the present invention is, on account of theabsence of a priori knowledge about the image, the implementation of amethod of segmentation based on active contours of a video image basedon elementary objects, in which the starting active contour, alsodesignated the starting contour, is arbitrary with regard to anelementary object of interest belonging to the image.

[0026] Another object of the present invention is also, having regard tothe initialization of the method which is the subject of the presentinvention from an arbitrary starting active contour, the implementationof a method for segmenting a video image which is extremely flexible touse and is extremely tolerant to the selection of an inexperienced user,the starting contour possibly containing several loops, in the absenceof any necessary orientation.

[0027] Another object of the present invention is also theimplementation of a method for segmenting an image based on activecontours, in which, all a priori knowledge about the image having beendeleted, the external energy term is consequently deleted, therebymaking it possible to obtain very fast convergence of the current activecontour to the natural contour of the elementary object of interest.

[0028] Another object of the present invention is also theimplementation of a method for segmenting an image based on activecontours, in which, on account of the absence of a priori knowledgeabout the image, a better tolerance to noise and to poorly defined imagecontours is obtained.

[0029] Another object of the present invention is also theimplementation of a method for segmenting an image based on activecontours, in which, on account of the tolerance of a starting contour toseveral loops, the segmentation of the image with regard to at least oneelementary object having several components can be implemented, therebyconferring a high degree of flexibility of use on the method which isthe subject of the present invention.

[0030] Another object of the present invention is the implementation ofa method for segmenting a video image based on elementary objects, inwhich the speed of convergence of the starting contour to the naturalcontour of the elementary object of interest in the image permits highstability of the process of segmentation in each image, and,consequently, stable tracking or following of moving objects oversuccessive images, thereby making it possible to obtain very robusttracking of a moving object of interest over a large number ofsuccessive images.

[0031] In particular, another object of the present invention is alsothe implementation of a method for segmenting a video image based onelementary objects, in which, on account of the speed of convergence ofthe active contours, of the robustness in the following of the movingobjects and of the tolerated subdividing of an active contour intoseveral active contours, each active contour resulting from such asubdivision evolves independently since it is linked only to thesubdivision of the elementary object of interest.

[0032] Another object of the present invention is finally theimplementation of a method for segmenting a video image based onelementary objects, in which, by virtue of a simplified motion followingprocess, the convergence of the current active contour to the motion ofthe mobile elementary object of interest is accelerated.

[0033] The method for segmenting a video image based on elementaryobjects, which is the subject of the present invention, is noteworthy inthat it consists, with regard to at least one elementary objectdelimited by a natural contour of this video image:

[0034] in defining, around this elementary object, a starting contourcompletely surrounding said elementary object;

[0035] in defining, on the basis of said starting contour, an originalactive contour, formed by a set of nodes distributed on this startingcontour, each node being formed by a point belonging to this startingcontour and by an elastic energy function representative of the distanceseparating this node from a neighboring node;

[0036] in subjecting, with regard to a set of reference values which arerepresentative of the natural contour of this elementary object, theoriginal active contour to a convergent deformation under a blockingcondition which determines whether the contour is reached, by displacingtoward the natural contour of the elementary object at least one of thenodes of the original active contour, so as to generate a current activecontour, this current active contour being subjected iteratively to thisconvergent deformation so as to generate distinct successive currentactive contours as long as this displacement satisfies the non-blockingcondition and in halting any nodal displacement of this current activecontour otherwise. This makes it possible to generate a final currentactive contour substantially reproducing the natural contour of theelementary object.

[0037] The method which is the subject of the present invention can in aparticularly advantageous manner be implemented on the basis of programmodules and finds application to all processing of video imagesinvolving object-based segmentation and for which a coarse but reliablepreselection of the object to be segmented can be achieved.

[0038] Among the applications which can be envisaged, mention may bemade, nonlimitingly, of applications linked:

[0039] to the new multimedia services distributed over remote networks,such as the World Wide Web or local area networks, services such asimage or video searching, in the case of the archiving of audiovisualproduction. The attraction of such services is connected, on the onehand, with the quality of restitution of the contents, and, on the otherhand, with the power of the search engine, well suited to the nature ofthe broadcast media. Specifically, it may be noted that increasing theamount of information available is not sufficient since it becomescrucial to make access to it easier;

[0040] to audiovisual production; modern techniques of audiovisualproduction are calling evermore upon the composition of variousbackgrounds and of foreground video objects in order to construct filmscenes or television scenes. At present, the shooting of video objectsis a particularly unwieldy operation, requiring recourse to thechroma-key technique, this technique making it necessary in particularto film any object of interest on a uniform background of known color.The method which is the subject of the present invention, allowingparticularly flexible and fast segmentation of images based onelementary objects, allows production costs to be greatly reduced;

[0041] to interactive television, also designated enhanced television, afield in which, by virtue of the method which is the subject of thepresent invention and on account of its flexibility and robustness, overa large number of images of mobile objects, it is possible to select anobject or an actor present on the screen, to follow the latter overtime, during the unfolding of the action, and to have availablemultimedia information about this object or this actor;

[0042] to tools for creating multimedia content satisfying the MPEG-4standard. The aforesaid standard does not provide any procedure forsegmenting images based on elementary objects. The method which is thesubject of the present invention makes it possible to introduce asegmentation process, a natural extension of such an environment;

[0043] to videophony. When the transmission throughput becomes toolimited, on account of the congestion of the transmission networks, itis of the greatest interest to concentrate the visual informationtransmitted, and hence the throughput available to ensure the routingthereof, on objects or image zones carrying most information, inparticular the face of the people speaking, the aforesaid concentrationbeing implementable by virtue of the segmentation method which is thesubject of the present invention;

[0044] to video conferencing services, where, in addition to theapplications inherent to videophony, the applications in which one seeksan increase in the visual sensation of presence by syntheticreconstruction of a virtual meeting gathering together in one and thesame virtual place all the participants to the video conference are madeeasier, by virtue of the segmentation method which is the subject of thepresent invention.

[0045] The method which is the subject of the present invention will bebetter understood on reading the description and on looking at thedrawings hereinbelow in which:

[0046]FIG. 1a represents, by way of illustration, a general flowchart ofthe steps allowing the implementation of the method which is the subjectof the present invention;

[0047]FIG. 1b represents, by way of illustration, a detail ofimplementation of the method which is the subject of the presentinvention illustrated in FIG. 1a and consisting in creating, from nodesdefined on a starting contour, either an original active contour, or acurrent active contour;

[0048]FIG. 2a represents, by way of illustration, a preferrednonlimiting mode of implementation of the method which is the subject ofthe present invention in which management of the existence ofintersections and of the resolution applied to the current activecontour is introduced;

[0049]FIG. 2b represents, by way of illustration, a detail of theimplementation of a step of the method which is the subject of theinvention illustrated in FIG. 2a, in which an initialization of thedomain of calculation of gradient of image intensity over each currentactive contour is carried out;

[0050]FIG. 2c represents, by way of illustration, a detail of specificimplementation of a step of managing the existence of intersections overany current active contour;

[0051]FIG. 3a, represents, by way of illustration, a general flowchartof a motion estimation process applied to a current active contour inaccordance with the method which is the subject of the present inventionand making it possible to ensure the tracking of a moving object over aplurality of successive images, such as video or television images;

[0052]FIG. 3b represents, by way of illustration, a preferrednonlimiting mode of carrying out a step of refining the current activecontour relating to an object in motion such as represented in FIG. 3a;

[0053]FIG. 3c shows, by way of illustration, the parts of the object onwhich the motion estimation is carried out;

[0054]FIG. 3d is similar to FIG. 3c in a real example composed of twoplayers acting a ballet scene;

[0055]FIG. 4 represents, by way of illustration, a string of videoimages relating to a ballet scene played by two actors which shows theevolution of the current active contour and in which the final activecontour splits into two, respectively unites into one;

[0056]FIG. 5 represents, by way of illustration, a flowchart relating toa protocol for searching for an elementary object of interest in asequence of images stored in a database accessible on a server site froman access terminal.

[0057] The method for segmenting a video image based on elementaryobjects, which is the subject of the present invention, will now bedescribed in conjunction with FIG. 1a and the subsequent figures.

[0058] In a general manner, it is recalled that the method which is thesubject of the present invention is implemented on the basis of at leastone image IM, such as a video image, but preferably on the basis of asequence of images comprising at least one elementary object, denotedOBJ, animate or inanimate and delimited by a natural contour CN.

[0059] The method which is the subject of the present invention is basedon the fact that any elementary object OBJ present in an image, inparticular a video image, has a natural contour CN whose trace ismanifested on the relevant image by luminous intensity values exhibitingsubstantially a discontinuity all along the latter, this discontinuityhaving the effect of introducing a concept of differential intensitywith regard to the object itself or the direct environment of thisobject, and, in particular, a luminous intensity gradient value over thenatural contour of the object, and hence over this trace, exhibiting asubstantially stable value.

[0060] The method which is the subject of the present invention, havingregard to the aforesaid remark, thus has the object, based on a startingcontour which is absolutely arbitrary but which surrounds this object,of searching, by deformation of this starting contour, by contraction ofthe latter to the aforesaid object, for a positional stability of theactive contour on the natural contour of the object.

[0061] With this aim, and as represented in FIG. 1a, on the basis of avideo image IM or of a plurality of successive images with regard to anelementary object OBJ exhibiting a natural contour CN at a starting stepS, the method which is the subject of the present invention consists, ina step A, in defining around the aforesaid elementary object OBJ, astarting contour, denoted CD, completely surrounding the elementaryobject OBJ.

[0062] As far as the definition of the starting contour CD is concerned,it is indicated of course that the image IM available in the form of avideo image, and hence in the form of an image file, can advantageouslybe displayed on a display system, not represented in the drawing in FIG.1a, such as a video screen furnished with a graphical interface and witha pointer. Under these conditions, and in a particularly simple manner,the image displayed being on the aforesaid display monitor, a user caneasily, on the basis of a pointing device, trace around the object OBJany starting contour CD surrounding the aforesaid object in the easiestmanner.

[0063] The aforesaid step A is then followed by a step B consisting indefining, on the basis of the starting contour CD, an original activecontour, denoted CAO, formed by a set of nodes distributed around thisstarting contour.

[0064] The step B is then followed by a step C of convergent deformationof the original active contour CAO by displacing at least one of thepoints of the original active contour CAO toward the elementary objectOBJ, and in particular toward the natural contour of the elementaryobject.

[0065] In accordance with a noteworthy aspect of the method which is thesubject of the present invention, the deformation of the original activecontour CAO is performed by displacing toward the natural contour of theelementary object at least one of the nodes of the original activecontour, this displacement being normal and centripetal to the originalcontour CAO, dependent on the elastic energy (or spring term) obtainedon the basis of the distance of the adjacent nodes from the current nodeand controlled by a blocking function on the image of the contours,which is obtained from the intensity measured along the segmentsadjacent to the current node.

[0066] The deformation of the original active contour CAO makes itpossible to generate a current active contour, denoted CAC, which isthen subjected iteratively to the aforesaid convergent deformation so asto generate distinct successive current active contours as long as thedisplacement and the deformation do not satisfy the blocking conditionfor all the nodes of the contour.

[0067] The final active contour substantially reproduces the naturalcontour CN of the elementary object OBJ.

[0068] In FIG. 1a, represented in step C is the deformation operationdescribed above for generating a current active contour.

[0069] Of course, in step B, that is to say immediately after thecreation of the starting contour CD, and on the basis of the plot of thelatter, and of the definition of the original active contour CAO, acalculation of the energy function E is carried out, this energyfunction being linked to the luminous intensity gradient calculated overthe original active contour CAO, as will be described later in thedescription.

[0070] Likewise, in step C, the application of a convergent deformationby displacing at least one point or node of the original active contourCAO, makes it possible to calculate an energy variation ΔE of minimumelastic energy, for the current active contour CAC obtained through thedeformation applied.

[0071] Step C can then be followed by a test step D consisting inverifying that the energy variation ΔE is a minimum.

[0072] Upon a positive response to the test D, the deformation processis re-engaged by iteration, by way of a return to step B, the currentactive contour CAC being however taken as original active contour CAOfor the next iteration. In FIG. 1a, the iteration is initiated by stepE, which is denoted:

CAO≡CAC.

[0073] Through this operation, it is indeed understood that theconvergent deformation process applied on the basis of step B, in whichthe original active contour CAO has been replaced by the current activecontour CAC of the previous iteration, can then be reapplied by way ofstep C and of step D which were described above.

[0074] The deformation process is then applied iteratively for as longas there is displacement, this allowing the successive current activecontours to approach closer to the natural contour of the object CN.

[0075] Under these conditions, in a step F, all displacement beingstopped, the current active contour CAC of the previous iterationcorresponds to a final active contour which is none other than thenatural contour of the object OBJ substantially.

[0076] A more detailed description of step B for defining, either anoriginal active contour CAO from the starting contour CD, or ifappropriate a current active contour CAC, will now be given inconjunction with FIG. 1b.

[0077] In a general manner, it is indicated that the set of the nodes ofeach active contour, original active contour CAO, respectively currentactive contour CAC, can advantageously be defined by polygonal modelingby sampling over the trace of the active contour, original activecontour CAO, respectively current active contour CAC, as a function ofthe distance between consecutive nodes.

[0078] Thus, with reference to FIG. 1b, and for a starting contour CDfor example, intended to generate an original active contour CAO, twoconsecutive nodes, denoted X₁ and X₂ are considered, and the length ofthe segment d between the nodes X₁ and X₂ is measured. This operation isrepresented in substep 1. To preserve as node a node X₂ neighboring afirst node X₁ as a function of the value of the aforesaid distance d,two threshold values Smax and Smin are introduced, satisfying therelation:

Smin<Smax

and

Smin=Smax/2

[0079] It is indicated that, in a general manner, the aforesaidthreshold values, designated polygonal sampling threshold values, can bedefined by the user. However, and in a nonlimiting manner, the polygonalsampling threshold values can be effected in a substantially automaticmanner on the basis of reference dimensions chosen as a function of thesize of the elementary object.

[0080] If the length of the segment d exceeds the threshold value Smax,as represented in substep 2, then an intermediate node X₃ is addedsubstantially in line with the middle of the segment d on the startingcontour CD. The node X₃ is then taken into account and inserted betweenthe nodes X₁ and X₂ so as to in fact construct the original activecontour CAO, if appropriate the current active contour CAC.

[0081] However, and in a nonlimiting manner, more sophisticated samplingand polygonal modeling procedures can be implemented, such asinterpolation or smoothing procedures (spline, by way of example), so asto add differential constraints on the original active contour,respectively the current active contour.

[0082] If conversely, the length of the segment d is less than the valueSmin, the corresponding segment is then merged, the nodes X₁ and X₂ thenbeing brought to a single resulting node X₄ represented in substep 4,positioned substantially in line with the middle of the segment oflength d on the starting contour or on the original active contour CAO,respectively the current active contour CAC. An interpolated positionother than that corresponding to the middle of the segment of length dcan be used. Of course, the nodes X₁ and X₂ are then deleted andreplaced by the single node X₄, as represented in substep 4.

[0083] The process of polygonal modeling by sampling as represented insubsteps 1 to 4 of FIG. 1b is repeated for an original active contourCAO, respectively a current active contour CAC until the distancebetween two consecutive nodes of the set of nodes adopted to constructthe original active contour CAO, respectively the current active contourCAC, lies in the interval defined by the polygonal sampling thresholdvalues.

[0084] One thus has, as represented in substep 2, a current activecontour CAC or an original active contour CAO modeled by the set ofsegments such as represented in FIG. 1b in the aforesaid substep,successive segments d₃₁, d₃₂, and so on and so forth over the entireplot of the original active contour, respectively of the current activecontour.

[0085] A more detailed description of the mode of calculating theblocking function will now be given hereinbelow.

[0086] For an elementary zone of the image consisting of a rectanglecomprising a specified number of pixels in the horizontal direction,respectively vertical direction, a luminous intensity gradient iscalculated in the horizontal direction, respectively vertical direction,the luminous intensity gradient or luminance gradient satisfyingrelation (1): ${GR}\left\{ \begin{matrix}{{{I_{x}\left( {i{,\quad j}} \right)} = \frac{{I\left( {i + {1,\quad j}} \right)} - {I\left( {i - {1,\quad j}} \right)}}{2}}\quad} \\{{I_{y}\left( {i,\quad j} \right)} = \frac{{I\left( {{i,\quad j} + 1} \right)} - {I\left( {{i,\quad j} - 1} \right)}}{2}}\end{matrix} \right.$

[0087] In the above relation, I_(x)(i,j) denotes the value of theluminous intensity gradient or luminance gradient in the horizontaldirection, and I_(y)(i,j) denotes the value of the luminous intensitygradient in the vertical direction for any pixel with coordinates i, jin the relevant rectangular zone of pixels considered with respect tothe adjacent pixels of address i+1, i−1, respectively j+1 and j−1.

[0088] The norm N of the gradient GR is then given by relation (2):$N = \sqrt{{I_{x}^{2}\left( {i,\quad j} \right)} + {I_{y}^{2}\left( {i,\quad j} \right)}}$

[0089] based on the gradients in the aforesaid vertical and horizontaldirections.

[0090] In accordance with a noteworthy aspect of the method which is thesubject of the present invention, the force of an active contour ismeasured by the norm N of the gradient as calculated above.

[0091] To evaluate the force of an active contour, original activecontour CAO, respectively current active contour CAC, for each node X ofthe active contour, the contributions of the luminous intensity gradientare evaluated respectively on the two segments adjacent to the relevantnode, that is to say on the segments d₃₁ and d₃₂ for the successivenodes represented in substep 2 of FIG. 1b.

[0092] The aforesaid segments being defined solely by their two ends,the positions of the intermediate points are calculated on the image bythe BRESENHAM algorithm.

[0093] For each node of a segment such as the nodes X₁, X₃ or X₂represented in the aforesaid FIG. 1b, the contribution is sampled offfrom the set of gradient values GR stored, this set being designated thegradients map. The contribution for the relevant node is then weightedby a shape function which equals 1 on the current node and decreaseslinearly to the value 0 on the adjacent node. All the gradientcontributions on the relevant segment are added up. The valuesassociated with each segment are stored in a vector.

[0094] Thus, with reference to FIG. 1b, for substep 2, and forconsecutive nodes X₁ and X₃ of the active contour which are separated bythe segment d₃₁, the weighting function p relating to the current pointx belonging to the polygonal modeling segment d₃₁ of the active contourCAO or CAC, satisfies relation (3):

p(X)=1−d(X,X ₁)/d(X ₃ ,X ₁)

[0095] In the above relation, X₁ and X₃ are consecutive nodes, X denotesthe current point belonging to the segment formed by X1 and X3, andd(Xa, Xb) denotes the distance between the nodes Xa and Xb.

[0096] The elastic energy function or functional representative of thedistance separating each node from a neighboring node then satisfiesrelation (4):

E=k.└(X−X _(p))²+(X−X _(s))²┘

[0097] In the above relation, X, Xp and Xs are respectively vectors ofdimension 2 containing the coordinates of the current node, of theprevious node and of the next node. k represents a stiffness term, theso-called spring term, corresponding to the elastic energyrepresentative of the distance separating each node from a neighboringnode.

[0098] Thus, a spring term, dependent on the derivative of the energy E,and corresponding to an energy variation ΔE is available for therelevant current node X on the original active contour CAO, respectivelythe current active contour CAC.

[0099] The spring term satisfies relation (5):

{overscore (R)}=k.[(X _(p) −X)+(X _(s) −X)]

[0100] In this relation, X_(p), X_(s) and X denote the same parametersas in the case of relation (4), k also denoting a stiffness constant.

[0101] The spring term {right arrow over (R)} tends to minimize theenergy E which is manifested as a smoothing, the force of which isweighted by the stiffness term k. This term is a regulating term whichavoids degeneracies and which eliminates in particular the formation offolds.

[0102] It is indicated that the spring term {right arrow over (R)} is anoriented quantity, supported by the segment joining two consecutivenodes and supported by it. In FIG. 1b the spring terms have been denoted{right arrow over (R)}₁₃, {right arrow over (R)}₃₁, {right arrow over(R)}₃₂, {right arrow over (R)}₂₃ in substep 2.

[0103] In accordance with a noteworthy aspect of the method which is thesubject of the present invention, the deformation applied to eachoriginal active contour CAO, respectively current active contour CAC, iseffected by a displacement of at least one of the constituent nodes ofthe original active contour, respectively of the relevant current activecontour, having regard to a relation linking, on the one hand, theaforesaid spring term {right arrow over (R)}, the displacement proper,in a centripetal direction toward the elementary object and of course aluminous energy term linked to the gradient and designated as thecontribution of the gradient on the original active contour CAO,respectively the current active contour CAC, as will be describedhereinbelow.

[0104] For each node of the relevant active contour, original activecontour CAO, respectively current active contour CAC, the value of theluminous intensity gradient is taken into account on the whole of eachsegment placed either side of the relevant node, the contribution G ofthe luminous intensity gradient GR on each relevant segment beingevaluated on the basis of summation of the norm of the gradient weightedby the weighting function mentioned previously in the description.

[0105] Thus, the contribution of the gradient on a given segment,segment modeling the relevant active contour by polygonal modeling, thensatisfies relation (6):$G = {\sum\limits_{\quad d}^{\quad}\quad {{p(x)} \cdot {N(x)}}}$

[0106] In the above relation, X, p(x) and N(x) respectively denote thecurrent point, the weighting associated with this point X and the norm,calculated at this point, of the gradient.

[0107] Thus, in FIG. 1b, in substep 2, d takes the value d31 and X movesfrom node X1 to node X3 over the segment d31.

[0108] The relation linking the displacement constraint {right arrowover (F)} applied at each node or at at least one node of the originalactive contour CAO, respectively of the current active contour CAC, willnow be described when the displacement of the relevant node is effectedin the direction N normal to the active contour at the level of therelevant node.

[0109] To calculate the direction normal to the relevant node, aheuristic is used, so as to assign a vector normal to the aforesaidactive contour. With reference to FIG. 1b, and by way of nonlimitingexample, for the node X₃ whose adjacent nodes are the nodes X₁ and X₂,the normal vector N₁ for the segment d₃₁ and the normal vector N₂ forthe segment d₃₂ are calculated. The mean or resultant of the normalizednormal vectors N₁ and N₂ yields the direction of the resultant normalvector N₃ at the node X₃. The value N₃ corresponding to a displacementvector {right arrow over (N)} is then oriented toward the inside of theobject, on the basis for example of a calculation of concavity of theplot supporting the original active contour CAO, respectively thecurrent active contour CAC. Other modes of calculation based on splineinterpolations or the like may be implemented for the estimation of thenormal vector {right arrow over (N)}.

[0110] Thus, for any normal vector {right arrow over (N)} and for aspring term {right arrow over (R)}, the displacement constraint {rightarrow over (F)} applied according to the displacement vector {rightarrow over (N)} at at least one of the nodes of the original activecontour, respectively of the current active contour, is given byrelation (7):

{right arrow over (F)}=({right arrow over (R)}+{right arrow over(N)})Π(G<S)

[0111] In the above relation, it is indicated that the term Π(G<S) is aspecific function such that this function is equal to 1 if G<S, andequal to 0 otherwise, S denoting a threshold value predefined by theuser and G denoting the contribution of the gradient at the relevantnode.

[0112] Thus, the aforesaid relation (7) defines the condition ofblocking of the displacement of the nodes by the function Π(G<S). Ifthis function is equal to 1, the displacement of the node or nodes ofthe current active contour by the resultant value {right arrow over (F)}is carried out and if this function is equal to zero the displacement ishalted.

[0113] Thus, if the contribution of the gradient G for the relevantcurrent node is less than the aforesaid threshold value S, the node, andof course, if appropriate, the set of constituent nodes of the originalactive contour CAO, respectively of the current active contour CAC, isdisplaced by the value of the displacement constraint {right arrow over(F)} in the centripetal direction defined for the relevant node.

[0114] A more detailed description of a preferred mode of implementationof the method which is the subject of the present invention will now begiven in conjunction with FIG. 2a. In the aforesaid figure, the samesteps, as defined in FIG. 1a, are denoted by the same references.

[0115] As far as step A is concerned, which consists in defining astarting contour CD around the object OBJ, this step, as is representedin the aforesaid FIG. 2a, can advantageously comprise a substep A₁₁consisting in an operation of smoothing the image by means of afiltering process. Thus, the current video image is filtered with theaim of limiting the ambient noise present in this image and of obtainingcontours which are more spread. The filtering used can consist of aconventional filtering process for eliminating noise as a function ofthe nature of the constituent data of the image. For this reason, thefiltering process will not be described in greater detail.

[0116] Substep A₁₁ can then be followed by a substep A₁₂ consisting, onthe basis of the starting contour CD, of an initialization of thecalculation of the gradient values for a specified zone of the image. Itis understood in particular that in order to limit the calculationtimes, the gradient values given by relations (1) and (2) above arecalculated only over the region enclosed by the starting contour CD,then by the successive current active contours until of course thecurrent active contour CAC reaches the final active contourcorresponding to the natural contour of the object. The calculationvalues for the norm of the gradient are then stored in a gradients map.The aforesaid values can be calculated as gray level or as color. By wayof nonlimiting example, it is indicated that the gradients map is animage of floating values initialized to an arbitrary value for example.

[0117] Represented in FIG. 2b are successive views on a display monitorof a video image comprising an object OBJ, an original active contourCAO or a current active contour CAC, and a zone in which the gradientsmap CG is calculated. It is understood in particular that the gradientsmap is calculated in a zone intermediate to the current active contourand to the natural contour of the object CN, this zone being representedshaded gray in FIG. 2b.

[0118] As far as step B of defining an original active contour CAO fromthe starting contour CD is concerned, it is indicated that this step canalso be subdivided into a first substep B₁₁ consisting in performing thesampling for polygonal modeling of the relevant contour, as representedin FIG. 1b, substep B₁₁ possibly then advantageously being followed by asubstep B₁₂ of detecting intersections on the active contour, originalactive contour CAO, respectively current active contour CAC. Substep B₁₂can advantageously be implemented when the elementary object consists ofan animate object in the image, and hence one which is capable ofmotion, of deformation and of partition, for any active contour capableof constituting a loop exhibiting at least one point of intersectionfollowing a partition, a deformation of this elementary object intoelementary object components.

[0119] When an intersection is detected, the active contour, originalactive contour, respectively current active contour, is then split andgrouped into a number of distinct active contours which is equal to thenumber of intersections plus one unit, so as to make it possible toassign a final active contour to each component of the aforesaidelementary object.

[0120] A specific modus operandi allowing the implementation of substepB₁₂ of detecting intersections will now be described in conjunction withFIG. 2c.

[0121] With reference to the aforesaid figure, it is indicated that anactive contour evolves over time, on account of the modifications ofshape or partition of the object, thereby causing loops possibly toappear within the active contour.

[0122] In a general manner, it is indicated that the auto-intersectionsof the active contour, original active contour CAO, respectively currentactive contour CAC, are measured over all the segments taken pair wise,the segments being formed between two consecutive nodes defining eachactive contour.

[0123] Thus, for A, B, C and D denoting four nodes constituting thesegments AB and CD respectively, AB=A+r (B−A) and CD=C+s(D−C) are thenobtained.

[0124] An intersection is then detected between the segments AB and CDif r and s belong to the interval [0, 1]. The values of r and of s aretherefore calculated by means of the following relation (8):$\begin{matrix}{r = \frac{{\left( {A_{y} - C_{y}} \right)\left( {D_{x} - C_{x}} \right)} - {\left( {A_{x} - C_{x}} \right)\left( {D_{y} - C_{y}} \right)}}{{\left( {B_{x} - A_{x}} \right)\left( {D_{y} - C_{y}} \right)} - {\left( {B_{y} - A_{y}} \right)\left( {D_{x} - C_{x}} \right)}}} \\{s = \frac{{\left( {A_{y} - C_{y}} \right)\left( {B_{x} - A_{x}} \right)} - {\left( {A_{x} - C_{x}} \right)\left( {B_{y} - A_{y}} \right)}}{{\left( {B_{x} - A_{x}} \right)\left( {D_{y} - C_{y}} \right)} - {\left( {B_{y} - A_{y}} \right)\left( {D_{x} - C_{y}} \right)}}}\end{matrix}$

[0125] In the above relation, the subscripts x and y associated with theletters A, B, C and D denote the ordinate and abscissa respectively ofthese letters.

[0126] In the case of the existence of an intersection between the nodesA, B and C, D in FIG. 2c, the current, respectively original, activecontour is divided into several active contours according to thedivision rule cited above. In the case of the existence of anintersection, by way of nonlimiting example, at the node I belonging tothe segments AB and CD in FIG. 2c, node A is disconnected from node Band the same holds for node C in relation to node D. Thereafter, node Aand node C are connected to node D, respectively to node B. It isrecalled that the concept of connection consists in constructing eachactive contour, original active contour, current active contour, in theform of a closed list of nodes.

[0127] The aforesaid step is a recursive process comprising the creationof a new active contour, the addition of the nodes lying between thenodes B and C in this new active contour and the simultaneous deletionof these same nodes from the current active contour. If the new activecontour is not degenerate, that is to say if it comprises at least morethan two nodes, then, it is stored in the form of a meta-snakerepresenting a vector of active contours, the latter themselves beingstored in the form of a list of nodes. An active contour is sensible toapproximate the exterior contours of an object. The aforesaid recursivefunction is called again until there is no intersection. Differentprocesses for intersection detection can be implemented withoutdeparting from the scope of the subject of the present invention.

[0128] Step D consisting in performing the test of minimum displacementcan advantageously, as represented in FIG. 2a, upon a negative responseto the aforesaid test, be followed by a step F₁ aimed at modifying thevalue of the resolution of definition of the current active contour CAC.Specifically, through an increase in the aforesaid resolution, resultingin a decrease in the inter-node distance and an increase in the numberof constituent nodes of the relevant current active contour CAC, it ispossible to recommence the process by way of a comparison step F₂pertaining to the number of passes, a positive response to step F₂allowing a return to step B on the basis of a current active contour CACwhose resolution has been increased in step F₁.

[0129] As far as the increase in resolution is concerned, in step F₁, itis indicated that the latter can be performed as described previously inthe description in conjunction with FIG. 1b, and in particular bymodifying the polygonal sampling threshold values Smax and Smin.

[0130] Conversely, on a negative response to the test step F₂, the stepof stopping displacement of final active contour F is then called, thefinal active contour being presumed to correspond to the natural contourof the elementary object of interest.

[0131] A more detailed description of a process for tracking anelementary object consisting of an animate object moving in the image,allowing the implementation of the method which is the subject of thepresent invention will now be given in conjunction with FIG. 3a and thefollowing figures.

[0132] In a general manner, it is indicated that the method which is thesubject of the present invention must make it possible to follow ortrack the elementary object given the fact that the latter is capable ofdeforming, of rotating and, more generally, of moving in the course oftime, that is to say from one image to the next, over a sequence ofvideo images for example.

[0133] Within the framework of the implementation of the method which isthe subject of the present invention, it is considered that the user hasselected an elementary object of interest, that is to say that step B ofFIG. 1a has been implemented, and, furthermore, that the acquisition ofthe elementary object of interest has been performed, that is to saythat step F of FIG. 1a or 1 b has been carried out, the final contoursatisfactorily hugging the elementary object of interest.

[0134] As represented in FIG. 3a, the method which is the subject of thepresent invention then consists, in a so-called data preparation step G,carried out on the current image, by constructing the mask of the objectdelimited by the final active contour or a band, called a ring,encompassing the nodes of the relevant active contour, the ring being adifference of the regions encompassed by two dilatations of the activecontour or by successive dilatations of a binary image initialized withthis active contour.

[0135] Step G is itself followed by a step H consisting in performing onthe ring, a motion estimation making it possible to displace the nodesof the active contour or the pixels of the ring according to anestimated motion vector.

[0136] A test I can be envisaged in such a way as to repeat the motionestimation, by return J to the motion estimation prior to step H. Thetest I can correspond for example in a motion estimation over a numbergreater than two images, for example, as a function of the user'schoice, as will be described later in the description.

[0137] On a negative response to the test I, the estimation of themotion not being repeated, the motion vector or displacement vector isthen applied to the relevant active contour, so as to make it possibleto ensure the following of the moving elementary object by the finalactive contour and to discriminate the aforesaid moving elementaryobject, having regard to the motion of the latter in the next image. Itis understood in particular that, for the next image, the method whichis the subject of the present invention can be repeated so as to carryout step B of FIG. 1a or of FIG. 2a, then step C of deformation bydisplacement under blocking condition for all the nodes of the contour.

[0138] However, as represented in FIG. 3a, step H of estimation ofmotion can be implemented according to two substeps, a first substep H₁of estimation of the motion proper applied to the dilated activecontour, as mentioned previously, followed by a substep H₂ consisting inrefining the segmentation of the image, that it is to say of theselection of the contour of the elementary object.

[0139] As far as the calculation of the estimation of the motion properis concerned, the theoretical indications hereinbelow will be explained.

[0140] The motion estimation procedure proper, implemented in step H₁for example, can be based on a multiresolution structure estimating theglobal motion of an object constituted by the current active contourCAC, by a translation model or an affine model. The multiresolution isobtained by successively filtering the images, this process making itpossible to accelerate the convergence of the solution and rendering thelatter more robust.

[0141] The transformation equations for a motion estimation model are asfollows, and satisfy relation (9):

[0142] Translation: $\quad\left\{ \begin{matrix}{x^{\prime} = {x + {dx}}} \\{y^{\prime} = {y + {dy}}}\end{matrix} \right.$

[0143] Affine Transformation: $\quad\left\{ \begin{matrix}{x^{\prime} = {{a_{1}x} + {a_{2}x} + a_{3}}} \\{y^{\prime} = {{a_{4}x} + {a_{5}y} + a_{6}}}\end{matrix} \right.$

[0144] In the above relation, x and y denote the coordinates of a pointM(x,y) of the current image, transformed owing to the motion of theelementary object into a point M′(x′,y′) with coordinates x′ and y′ inthe next image, dx, dy denote the parameters of translation in thehorizontal x, and vertical y directions for the translationaltransformation, and a₁, a₂, a₃, a₄, a₅, a₆ denote the affinetransformation parameters making it possible to go from the currentactive contour of the current image to the current active contour of thenext image owing to the displacement or deformation of the elementaryobject of interest.

[0145] As far as step G of data preparation is concerned, that is to sayof defining the ring forming band from the current active contour or thefinal active contour segmenting the elementary object of interest, it isindicated that the aforesaid step can consist in generating a binaryimage calculated over the aforesaid ring encompassing the nodes of theaforesaid final active contour CAF. The previously mentioned ring cancorrespond to the difference of the regions encompassed by twodilatations of the final active contour CAF, these regions beingdefinable with respect to the geometrical center of the active contouror to the center of gravity of the latter. Another possibility canconsist in obtaining the aforesaid regions through successivedilatations of a binary image initialized on the basis of the relevantfinal active contour CAF.

[0146] Having regard to these indications, it is indicated that the datapreparation carried out in step G can thus consist in establishing:

[0147] the mask delimiting the region over which the estimation iscarried out;

[0148] the number of levels of the multiresolution used to execute themotion estimation;

[0149] the type of estimation by affine transformation or translation.

[0150] The substep of refining the object contour selection carried outin substep H₂ can consist, as described in conjunction with FIG. 3b,following the estimation of the motion of the ring of the relevantactive contour, the final active contour CAF for example, constituting acurrent active contour CAC in respect of the estimation of the motion,in displacing each node of this active contour CAC by the value of theestimated motion in a substep H₂₁, so as to generate an initial activecontour for the new image. Represented in FIG. 3b is the final activecontour forming in fact a current active contour CAC by a dashed circle,in a nonlimiting manner, so as not to overburden the drawing, the motionestimation having given rise to a displacement vector {right arrow over(D)}e and the displacement being illustrated symbolically by thedisplacement of the center of the current active contour CAC, and ofcourse of the latter's periphery. This displacement makes it possible togenerate a displaced current active contour CACD at the end of step H₂₁.The displaced current active contour CACD thus constitutes an initialcurrent active contour CACI for the next image.

[0151] Substep H₂₁ is then followed by a substep H₂₂ consisting indilating the initial current active contour CACI by geometricaltransformation, so as to generate a displaced and dilated current activecontour CACDd constituting a reference initial active contour CAIR forthis next image. The dilatation process is carried out by geometricaltransformation, the geometrical transformation possibly consisting forexample in a homothety with respect to the barycenter of the displacedcurrent active contour CACD. The reference initial active contour CAIRthus obtained constitutes an original active contour of the elementaryobject for the next image in substep H₂₃, this of course making itpossible to iteratively recommence the convergent deformation of theoriginal active contour so as to generate the final current activecontour for the aforesaid next image. It is thus understood that,following substep H₂₃ of FIG. 3b, it is then possible to call forexample step B then step C of FIGS. 1a and 2 a so as to ensure thesegmentation of the object, in accordance with the method which is thesubject of the present invention.

[0152] Represented in FIG. 3c is any active contour, a mask consistingof a binary image and finally, the ring corresponding to successivedilatations of a binary image initialized with the active contour.

[0153] Finally, represented in FIG. 3d is an elementary object ofinterest formed by two players acting a ballet scene, the final activecontour CAF surrounding the two players then the ring obtained aroundthem, by virtue of the implementation of step G of FIG. 3a.

[0154] Finally, FIG. 4 represents a ballet scene acted by the aforesaidtwo players. The first two images on top depict two possible selectionsof the players (mouse and encompassing box) encompassing the players andthe other six images depict an instant of the temporal tracking of theseplayers.

[0155] A description of a protocol for searching for an elementaryobject of interest in one or more video images stored in a databaseaccessible through a server site on the basis of the segmentationmethod, which is the subject of the present invention, this search beingconducted from a terminal for access to this server site, will now begiven in conjunction with FIG. 5.

[0156] In a general manner, and with reference to the aforesaid figure,an access terminal, denoted TA, such as a terminal consisting of anoffice microcomputer, a portable microcomputer, a digital assistant ofPDA type, or a mobile radio telephony terminal furnished with a displayscreen and with a graphical interface of WAP type for example, thismobile radio telephony terminal implementing a transmission of UMTS typefor example, or GPRS type, and allowing the exchange of files with thisserver site are considered.

[0157] The terminal TA has available a sample, in fact consisting of asample image denoted IECH, consisting of at least one sample video imageemanating from the sequence of images or from the plurality of imagesstored in a database of the server SERV. The sequence of images storedin the database of this server in fact constitutes a sequence ofreference images, denoted SIR, this sequence of images being presumed tocomprise a plurality of current reference images IRC, each currentreference image being followed by a next reference image, denoted IRS.

[0158] With reference to the aforesaid FIG. 5, the protocol forsearching for an elementary object of interest, which is the subject ofthe present invention, consists, in a step K, in segmenting the samplevideo image IECH according to the method which is the subject of thepresent invention, as described previously in the description withreference to FIGS. 1 to 4. The aim of this segmentation is to generateat least one sample active contour. This sample active contour is forexample a final active contour CAF, within the meaning of the methodwhich is the subject of the present invention, and consisting of a listof nodes associated with the elementary object of interest belonging tothe sample video image IECH. It is recalled that the list of nodes infact constitutes a list of points distributed over the relevant activecontour, final active contour, with each point there being associatedmoreover a value of stiffness constant representative of the elasticenergy E, as mentioned previously in the description. For this reason,the sample active contour is denoted:

CAE=[{P_(i),K_(i)}]=L_(e)

[0159] where P_(i) denotes each point-of the active contour and K_(i)denotes the stiffness constant associated with this point to an adjacentpoint.

[0160] Step K is then followed by a step L consisting in transmittingthe list of nodes L_(e) from the access terminal TA to the server siteSERV.

[0161] The aforesaid step L is then followed by a step M consisting, atthe server level, in segmenting at least one current image of thesequence of images stored in the database, this segmentation of coursebeing performed in accordance with the segmentation method which is thesubject of the invention described previously in the description. Theaforesaid segmentation operation is denoted segmentation IRC, so as togenerate CAR, this operation of course making it possible to generate atleast one reference active contour, denoted CAR.

[0162] The reference active contour is denoted:

CAR=[{P_(j),K_(j)}]=L_(r)

[0163] It is of course understood that the list L_(r) constitutes thereference active contour, which is presumed to consist of the pointsP_(j) of this active contour and the stiffness term K_(j) which isassociated with each of these points.

[0164] Step M is then itself followed by a step N consisting of acomparison test step by comparison of similarity of the sample activecontour L_(e) with the reference active contour of the list L_(r),denoted L_(e)≅L_(r).

[0165] By comparison of similarity is meant a term-by-term comparison ofthe coordinates of the points P_(i) and P_(j) distributed over thesample active contour CAE, respectively over the reference activecontour ACAR, and of course by comparison of the corresponding stiffnessterms K_(i) and K_(j). the comparison can be carried out with aconfidence interval, in such a way as to introduce a comparison of fuzzylogic type making it possible to modulate the decision.

[0166] On a negative response to the test carried out in the comparisonstep N, the sample list and the sample active contour not being able tobe identified satisfactorily with the reference list L_(r) and with thereference active contour CAR, the search is continued over the nextreference image IRS by returning to the segmentation step M, to thevalue of the current image IRC there being allocated however the valueof the next image IRS through the equality IRC=IRS.

[0167] Conversely, upon comparison of similarity, the sample list andthe sample active contour CAE being able to be identified with thereference list L_(r) and with the reference active contour CAR, the testcomparison step N is followed by a step P consisting in stopping thesearch and in transmitting, if necessary, on request from the terminalTA, all or part of the sequence of images stored in the databaseaccessible on the server site SERV.

[0168] The protocol which is the subject of the present invention can beimproved in so far as, with each sample active contour CAE, and on theother hand, with each reference active contour CAR, can be associatedvarious attribute parameters of the elementary object which is thesubject of the search, so as to improve the object recognitionperformance.

[0169] With this aim, as represented also in FIG. 5, the protocol whichis the subject of the present invention can comprise steps consisting indiscriminating, in the object of interest, sample object componentattributes, denoted AECH, attributes such as color, texture, motionparameters, etc. of the elementary objet of interest in the relevantsample image. Specifically, while the sample active contour CAE isavailable, the final active contour CAF and, consequently, the naturalcontour of the object in question, is necessarily available. It is thenparticularly easy to calculate, in this natural contour, the aforesaidattributes on the basis of image processing and analysis procedures.

[0170] Furthermore, in step L, the sample object component attributesAECH are transmitted from the access terminal TA to the server siteSERV.

[0171] Furthermore, in step M, the protocol which is the subject of thepresent invention can consist in discriminating, in the object delimitedby the reference active contour, reference object component attributesof the same type as those of the sample object component attributes. Thereference object component attributes are denoted AIR and correspond inthe same way to attributes such as texture, color, color temperature orthe like, in the object delimited by the reference active contour.

[0172] Step M is then followed by a step N in which the reference objectcomponent attributes AECH and the sample object component attributes AIRare furthermore compared so as to instruct the stoppage, respectivelythe continuation of the search. It is understood in particular that thisinstruction can be carried out by a coupling by an AND function of thecomparison of the sample list and of the sample active contour with thereference list and with the reference active contour with the comparisonof the sample attributes with the reference object component attributes.

[0173] Of course, the comparison in respect of the aforesaid attributescan be carried out having regard to a confidence span, so as tointroduce a fuzzy logic decision, as mentioned previously in thedescription.

[0174] As far as the implementation of the step M of segmenting thecurrent reference image is concerned, it is indicated that the casewhere this image comprises several elementary objects of interest doesnot constitute an obstacle to the implementation of the protocol whichis the subject of the present invention, in so far as, in such a case,it is possible to provide arbitrarily for a starting active contour CDsubstantially surrounding the entire image at its periphery, the methodwhich is the subject of the present invention allowing a segmentationinto several elementary objects of interest when the latter aredisjoint. Consequently, and independently of the choice in the sampleimage IECH of an elementary object of interest by the user, there thusalways exists, in each current reference image IRC, a referenceelementary object corresponding substantially to the object chosen bythe user in the sample image IECH.

[0175] The protocol which is the subject of the present invention thusappears to be particularly well suited to the implementation of a searchfor an image in video image sequences in the MPEG 4 Standard forexample.

1. A method for segmenting a video image based on elementary objects,characterized in that it consists, with regard to at least oneelementary object delimited by a natural contour of this video image: indefining, around this elementary object, a starting contour completelysurrounding said elementary object; in defining, on the basis of saidstarting contour, an original active contour, formed by a set of nodesdistributed on this starting contour, each node being formed by a pointbelonging to this starting contour and by an elastic energy functionrepresentative of the distance separating this node from a neighboringnode; in subjecting, with regard to a set of reference values which iscapable of representing the natural contour of said elementary object,said original active contour to a convergent deformation, by displacingtoward the natural contour of the elementary object at least one of thenodes of the original active contour, so as to generate a current activecontour, this current active contour being subjected iteratively to saidconvergent deformation so as to generate distinct successive currentactive contours as long as said displacement satisfies the non-blockingcondition and in halting any nodal displacement of said current activecontour otherwise, thereby making it possible to generate a finalcurrent active contour substantially reproducing the natural contour ofsaid elementary object.
 2. The method as claimed in claim 1,characterized in that the set of nodes of each active contour is definedby polygonal modeling by sampling over the trace of the active contouras a function of the distance between consecutive nodes, thereby makingit possible to adapt the resolution of definition of each of thesuccessive active contours.
 3. The method as claimed in one of claims 1or 2, characterized in that said convergent deformation consists: incalculating at each of the nodes of the current active contour a vectornormal to the active contour; in subjecting at least one of the nodes ofsaid active contour to a centripetal displacement in the direction ofsaid normal vector associated with said node.
 4. The method as claimedin one of claims 1 to 3, characterized in that said set of referencevalues consists of a set of values of image intensity gradient,calculated over said active contour.
 5. The method as claimed in one ofclaims 1 to 4, characterized in that said elementary object beingconstituted by an animate object in the image, which animate object iscapable of motion, of deformation and of partition, for any activecontour capable of constituting a loop exhibiting at least one point ofintersection subsequent to a partition of said elementary object intocomponents of elementary objects, it consists: in detecting theexistence on said active contour of at least one intersection; insplitting/grouping said active contour into a number of distinct activecontours equal to the number of intersections plus one unit, therebymaking it possible to assign a final active contour to each component ofsaid elementary object.
 6. The method as claimed in one of claims 1 to5, characterized in that said elementary object being constituted by ananimate object moving in the image, it furthermore consists, for atleast two successive video images: in defining on each final activecontour of each image a band, forming a ring, encompassing the set ofnodes belonging to said active contour; in performing between points ofsaid ring an estimation of motion of the elementary object from theimage to the next image, making it possible to define a motion vectorover the nodes of said active contour; in applying, at each node of saidactive contour, said motion vector, to the next image, thereby making itpossible to track the moving elementary object by said final activecontour and to discriminate said moving elementary objet having regardto the motion of the latter.
 7. The method as claimed in claim 6,characterized in that, with the aim of refining the segmentation of theimage, it consists, subsequent to the estimation of the motion of thering of the active contour: in displacing each node of this activecontour by the value of the estimated motion so as to generate aninitial active contour for the new image; in dilating this initialactive contour, by geometrical transformation, so as to generate areference initial active contour for this new image, said referenceinitial active contour constituting an original active contour of thisobject; in iteratively recommencing the convergent deformation of saidoriginal active contour, so as to generate said final current activecontour.
 8. A protocol for searching for an elementary object ofinterest in a sequence of images stored in a database accessible on aserver site, from a terminal for access to this server site, this accessterminal being furnished with a sample consisting of at least one samplevideo image emanating from this sequence of images, characterized inthat it consists at least: in segmenting said sample video imagefollowing the method which is the subject of the present inventionaccording to one of claims 1 to 7, so as to generate at least one sampleactive contour constituted by a list of nodes associated with saidelementary object of interest belonging to this sample video image; intransmitting to said list of nodes from said terminal for access to saidserver site; in segmenting at least one current image of said sequenceof images stored in said database following the method which is thesubject of the present invention according to one of claims 1 to 7, soas to generate at least one reference active contour; in comparing, bycomparison of similarity, said sample active contour with said referenceactive contour and, on comparison of similarity, stopping the search soas to ensure the transmission of all or part of said sequence of storedimages to said access terminal, and continuing the search over everyimage following said current image in said sequence of stored imagesotherwise.
 9. The protocol as claimed in claim 8, characterized in thatit furthermore comprises the steps consisting in: discriminating, insaid object of interest, sample object component attributes such ascolor, texture, motion parameters, in said sample video image;transmitting said object component attributes from said access terminalto said server site; discriminating, in the object delimited by saidreference active contour, reference object component attributes of thesame type as those of the sample object component attributes; comparingthe reference object component attributes and the sample objectcomponent attributes so as to instruct the stoppage, respectively thecontinuation of the search.